code: def __call__(self, data):
      encoded_inputs_all = []
      seq_len = len(data["input_ids"])
      for index in range(0, seq_len, self.max_seq_len):
          chunk_beg = index
          chunk_end = min(index + self.max_seq_len, seq_len)
          encoded_inputs_example = {}
          for key in data:
              if key in [
                  "label",
                  "input_ids",
                  "labels",
                  "token_type_ids",
                  "bbox",
                  "attention_mask",
              ]:
                  if self.infer_mode and key == "labels":
                      encoded_inputs_example[key] = data[key]
                  else:
                      encoded_inputs_example[key] = data[key][
                          chunk_beg:chunk_end
                      ]
              else:
                  encoded_inputs_example[key] = data[key]
  
          encoded_inputs_all.append(encoded_inputs_example)
      if len(encoded_inputs_all) == 0:
          return None
      return encoded_inputs_all[0]
  
file_path: PaddleOCR/ppocr/data/imaug/vqa/token/vqa_token_chunk.py
imports: from collections import defaultdict
label_desc: Use image node_id 2 for calling the VQASerTokenChunk obj's underlying member method code with example usage: obj.__call__(data) and returns: encoded_inputs_all, None